一种基于RBF神经网络的汉语耳语音转化为正常语音的方法  

Reconstruction of Normal Speech from Chinese Whispered Speech Based on RBF Neural Network

作　　者：王海燕[1] WANG Hai-Yan(Electronic Engineering,Suzhou Industrial Park Vocational College,Suzhou Jiangsu 215021)

机构地区：[1]苏州工业园区职业技术学院,江苏苏州215021

出　　处：《数字技术与应用》2018年第9期49-51,共3页Digital Technology & Application

摘　　要：针对汉语耳语音特征参数较正常语音发生变化而导致的可懂度和清晰度较差的问题,提出了采用能够以任意精度逼近连续函数的RBF神经网络建立汉语耳语音到正常语音的频谱包络映射关系,用以修正汉语耳语音的线谱对参数的方法。实验结果表明采用本文方法的汉语耳语音MOS得分为3.6,频谱失真距离变小,可懂度和清晰度得到了较大的提高。As the characteristic parameters of the Chinese whispered speech are different from the normal speech,this paper establishes the relationship of spectral mapping between Chinese whispered and normal speech by using RBF neural network,which will modify the Linear spectral pair parameters.Simulation results show that the score of the mean opinion score(MOS)is 3.6;the distorted distance of bark spectrum is decreased.Both intelligibility and quality of the converted speech are greater improved.

关 键 词：RBF 汉语耳语音 线谱对参数 

分 类 号：TN912[电子电信—通信与信息系统]